Modeling the Behavior of Inflation Rate in Albania Using Time Series


  • Rozana Liko Faculty of Technical Science, University of Vlora



Autoregressive Conditional Heteroscedasticity, Generalized Autoregressive Conditional Heteroscedasticity, Inflation


In this paper, time series theory is used to modelling monthly inflation data in Albania during the period from January 2000 to December 2016. The autoregressive conditional heteroscedastic (ARCH) and their extensions, generalized autoregressive conditional heteroscedasticity (GARCH)) models are used to better fit the data. The study reveals that the inflation series is stationary, non-normality and has serial correlation.   Based on minimum AIC and SIC values the best model turn to be GARCH (1, 1) model with mean equation ARMA (2, 1)x(2, 0)12. Based on the selected model one year of inflation is forecasted (from January 2016 to December 2016).


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Author Biography

Rozana Liko, Faculty of Technical Science, University of Vlora

Department of Mathematics


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How to Cite

Liko, R. (2017). Modeling the Behavior of Inflation Rate in Albania Using Time Series. JOURNAL OF ADVANCES IN MATHEMATICS, 13(3), 7257–7263.